class_docstr: Tests the correctness of the Y = g(X) = Log[1 + exp(X)] transformation.
code: def testHingeSoftnessZeroRaises(self):
      with self.assertRaisesOpError(
          "Argument `hinge_softness` must be non-zero."
      ):
          self.evaluate(
              softplus.Softplus(
                  hinge_softness=0.0, validate_args=True
              ).forward(1.0)
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 4 for calling the SoftplusBijectorTest obj's underlying member method code with example usage: obj.testHingeSoftnessZeroRaises() without return types